Comprehensive curriculum from Fundamentals to Deep Learning
Complete Zero to Hero journey. CNNs, RNNs, LSTMs, Transformers, GANs, and Diffusion Models. Featuring rigorous "Paper & Pain" math and interactive visualizations.
The foundation. Regression, Classification, Clustering, SVMs, Decision Trees, and Ensembles. Master Scikit-Learn.
Hands-on laboratory for datasets, experimental scripts, and practical ML applications.
Calculus, Linear Algebra, and Probability. The engine room of AI. Derivatives, Matrix Operations, and Eigenvalues.
Descriptive and Inferential Statistics. Hypothesis testing, Distributions, P-values, and Bayesian concepts.
Data cleaning, transformation, scaling, encoding, and selection. The art of preparing data for models.
Matplotlib, Seaborn, Plotly. Communicating insights effectively through beautiful charts and dashboards.
Mastering LLMs. Zero-shot, Few-shot, Chain-of-Thought, and advanced prompting strategies for GPT-4/Claude.